The Role of Influenza in the Delay between Low Temperature and Ischemic Heart Disease: Evidence from Simulation and Mortality Data from Japan

Investigating the impact of extreme weather events and related indicators on cardiometabolic multimorbidity

BACKGROUND

The impact of weather on human health has been proven, but the impact of extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently explored.

OBJECTIVES

Investigating the impact of extreme temperature, relative humidity (RH), and laboratory testing parameters at admission on adverse events in CMM hospitalizations.

DESIGNS

Time-stratified case-crossover design.

METHODS

A distributional lag nonlinear model with a time-stratified case-crossover design was used to explore the nonlinear lagged association between environmental factors and CMM. Subsequently, unbalanced data were processed by 1:2 propensity score matching (PSM) and conditional logistic regression was employed to analyze the association between laboratory indicators and unplanned readmissions for CMM. Finally, the previously identified environmental factors and relevant laboratory indicators were incorporated into different machine learning models to predict the risk of unplanned readmission for CMM.

RESULTS

There are nonlinear associations and hysteresis effects between temperature, RH and hospital admissions for a variety of CMM. In addition, the risk of admission is higher under low temperature and high RH conditions with the addition of particulate matter (PM, PM2.5 and PM10) and O3_8h. The risk is greater for females and adults aged 65 and older. Compared with first quartile (Q1), the fourth quartile (Q4) had a higher association between serum calcium (HR = 1.3632, 95% CI: 1.0732 ~ 1.7334), serum creatinine (HR = 1.7987, 95% CI: 1.3528 ~ 2.3958), fasting plasma glucose (HR = 1.2579, 95% CI: 1.0839 ~ 1.4770), aspartate aminotransferase/ alanine aminotransferase ratio (HR = 2.3131, 95% CI: 1.9844 ~ 2.6418), alanine aminotransferase (HR = 1.7687, 95% CI: 1.2388 ~ 2.2986), and gamma-glutamyltransferase (HR = 1.4951, 95% CI: 1.2551 ~ 1.7351) were independently and positively associated with unplanned readmission for CMM. However, serum total bilirubin and High-Density Lipoprotein (HDL) showed negative correlations. After incorporating environmental factors and their lagged terms, eXtreme Gradient Boosting (XGBoost) demonstrated a more prominent predictive performance for unplanned readmission of CMM patients, with an average area under the receiver operating characteristic curve (AUC) of 0.767 (95% CI:0.7486 ~ 0.7854).

CONCLUSIONS

Extreme cold or wet weather is linked to worsened adverse health effects in female patients with CMM and in individuals aged 65 years and older. Moreover, meteorologic factors and environmental pollutants may elevate the likelihood of unplanned readmissions for CMM.

Estimated causal effects of common respiratory infections on cardiovascular risk: a meta-analysis

OBJECTIVE

Literature supports associations between common respiratory tract infections (RTIs) and risk of cardiovascular diseases, yet the importance of RTIs for cardiovascular risk management remains less understood. This systematic review and meta-analysis aimed to estimate the causal effects of RTIs on occurrence of cardiovascular diseases in the general population.

METHODS

MEDLINE and EMBASE were systematically searched up to 4 November 2022. Eligible were all aetiological studies evaluating risk of cardiovascular outcomes after exposure to common RTIs within any follow-up duration. Evidence was pooled using random-effects models if data allowed. The ROBINS-E and GRADE approaches were used to rate risk of bias and certainty of evidence, respectively. All assessments were performed in duplicate.

RESULTS

We included 34 studies (65 678 650 individuals). Most studies had a high risk of bias. COVID-19 likely increases relative risk (RR (95% CI)) of myocardial infarction (3.3 (1.0 to 11.0)), stroke (3.5 (1.2 to 10)), pulmonary embolism (24.6 (13.5 to 44.9)) and deep venous thrombosis (7.8 (4.3 to 14.4)) within 30 days after infection (GRADE: moderate) and about twofold within 1 year (GRADE: low to moderate). Other RTIs also likely increase the RR of myocardial infarction (2.9 (95% CI 1.8 to 4.9)) and stroke (2.6 (95% CI 1.1 to 6.4)) within 30 days (GRADE: moderate), and to a lesser extent with longer follow-up.

CONCLUSIONS

RTIs likely increase the risk of cardiovascular diseases about 1.5-5 fold within 1 month after infection. RTIs may, therefore, have clinical relevance as target for cardiovascular risk management, especially in high-risk populations.

PROSPERO REGISTRATION NUMBER

CRD42023416277.

Primary prevention of acute cardiovascular events by influenza vaccination: an observational study

AIMS

Previous studies show a reduced incidence of first myocardial infarction and stroke 1-3 months after influenza vaccination, but it is unclear how underlying cardiovascular risk impacts the association.

METHODS AND RESULTS

The study used linked Clinical Practice Research Datalink, Hospital Episode Statistics Admitted Patient Care and Office for National Statistics mortality data from England between 1 September 2008 and 31 August 2019. From the data, individuals aged 40-84 years with a first acute cardiovascular event and influenza vaccination occurring within 12 months of each September were selected. Using a self-controlled case series analysis, season-adjusted cardiovascular risk stratified incidence ratios (IRs) for cardiovascular events after vaccination compared with baseline time before and >120 days after vaccination were generated. 193 900 individuals with a first acute cardiovascular event and influenza vaccine were included. 105 539 had hypertension and 172 050 had a QRISK2 score ≥10%. In main analysis, acute cardiovascular event risk was reduced in the 15-28 days after vaccination [IR 0.72 (95% CI 0.70-0.74)] and, while the effect size tapered, remained reduced to 91-120 days after vaccination [0.83 (0.81-0.88)]. Reduced cardiovascular events were seen after vaccination among individuals of all age groups and with raised and low cardiovascular risk.

CONCLUSIONS

Influenza vaccine may offer cardiovascular benefit among individuals at varying cardiovascular risk. Further studies are needed to characterize the populations who could derive the most cardiovascular benefits from vaccination.

Ability to adapt to seasonal temperature extremes among atrial fibrillation patients. A nation-wide study of hospitalizations in Israel

BACKGROUND

In recent years, temperature fluctuations and adverse weather events have become major concerns, influencing overall mortality and morbidity. While the association between extreme temperatures and atrial fibrillation (AF) has been supported by research, there is limited evidence on the ability of AF patients to adapt to the changing temperatures. We explored this question among AF patients in Israel featured by extreme temperature conditions.

METHODS

We examined the association between exposure to extreme temperatures and hospitalizations related to AF in a nationwide cohort in Israel. A case-crossover design with a distributed nonlinear model (DLNM) was applied to assess possible effects of temperature fluctuations during each season. We considered the 7 days prior to the event as the possible window period.

RESULTS

During 2004-2018 we recorded a total of 54,909 hospitalizations for AF. Low temperatures in winter and high in summer adversely affected AF-related hospitalizations. The effect recorded for the first few weeks of each season was of higher magnitude and decreased or faded off completely as the seasons progressed (OR in winter: from 1.14, 95%CI 0.98, 1.32 to 0.90, 95%CI: 0.77, 1.06;OR in summer: from 1.95, 95%CI: 1.51, 2.52 to 1.22, 95%CI: 0.90, 1.65). Patients living in the south region and patients with low socioeconomic status were more susceptible to extreme temperatures.

CONCLUSIONS

Although extreme hot and cold temperatures are associated with an increased risk of hospitalization for AF, the patients are likely to adapt to temperature change over the course of the first weeks of the season.

Role of temperature, influenza and other local characteristics in seasonality of mortality: a population-based time-series study in Japan

OBJECTIVES

To investigate the extent to which temperature and influenza explained seasonality of mortality in Japan and to examine the association of the seasonality with prefecture-specific characteristics.

DESIGN

We conducted time-series analysis to estimate the seasonal amplitude before and after adjusting for temperature and/or influenza-like illness (ILI). Next, we applied linear mixed effect models to investigate the association of seasonal amplitudes with each indicator on prefecture-specific characteristics on climate, demographic and socioeconomic factors and adaptations.

SETTING

47 prefectures in Japan PARTICIPANTS: Deaths for all-cause, circulatory, and respiratory disease between 1999 and 2015.

OUTCOME MEASURES

Peak-to-trough ratio (PTR, a measure of seasonal amplitude).

RESULTS

The nationwide unadjusted-PTRs for all-cause, circulatory and respiratory mortality were 1.29 (95% CIs: 1.28 to 1.31), 1.55 (95% CI: 1.52 to 1.57) and 1.45 (95% CI: 1.43 to 1.48), respectively. These PTRs reduced substantially after adjusting for temperature but very little after a separate adjustment for ILI. Furthermore, seasonal amplitudes varied between prefectures. However, there was no strong evidence for the associations of PTR with the indicators on prefecture-specific characteristics.

CONCLUSIONS

Seasonality of mortality is primarily driven by temperature in Japan. The spatial variation in seasonal amplitudes was not associated with prefecture-specific characteristics. Although further investigations are required to confirm our findings, this study can help us gain a better understanding of the mechanisms underlying seasonality of mortality.

Intensified impacts on mortality due to compound winter extremes in the Czech Republic

Although impacts of extremely cold temperatures on human health have been widely studied, adverse effects of other extreme weather phenomena have so far received much less attention. We employed a high-quality long-term mortality time series (1982-2017) to evaluate impacts of extreme winter weather in the Czech Republic. We aimed to clarify whether compound events of extreme weather cause larger impacts on mortality than do each type of extreme if evaluated individually. Using daily data from the E-OBS and ERA5 datasets, we analyzed 9 types of extreme events: extreme wind gust, precipitation, snowfall, and sudden temperature and pressure changes. Relative mortality deviations from the adjusted baseline were used to estimate the immediate effect of the selected extreme events on excess mortality. The impact was adjusted for the effect of extreme cold. Extreme events associated with sudden rise of minimum temperature and pressure drops had generally significant impact on excess mortality (3.7% and 1.4% increase). The impacts were even more pronounced if these events occurred simultaneously or were compounded with other types of extremes, such as heavy precipitation, snowfall, maximum temperature rise, and their combinations (increase as great as 14.4%). Effects of some compound events were significant even for combinations of extremes having no significant impact on mortality when evaluated separately. On the other hand, a "protective" effect of pressure increases reduced the risk for its compound events. Meteorological patterns during extreme events linked to excess mortality indicate passage of a low-pressure system northerly from the study domain. We identified extreme winter weather events other than cold temperatures with significant impact on excess mortality. Our results suggest that occurrence of compound extreme events strengthen the impacts on mortality and therefore analysis of multiple meteorological parameters is a useful approach in defining adverse weather conditions.

Ambient temperature, seasonal influenza and risk of cardiovascular disease in a subtropical area in Southern China

BACKGROUND

Given the regular winter recurrence of influenza epidemics and the biologically plausible association between seasonal influenza and cardiovascular events, researchers assumed a valid and reliable influenza forecast could envision the timing and burden of winter surge in cardiovascular (CVD) hospitalizations. This, however, is well justified only in temperate regions. In this study, we aim to investigate the temporal association between ambient temperature, seasonal influenza and risk of cardiovascular events in a subtropical city.

METHODS

Generalized additive model was used in conjunction with distributed-lag non-linear model of quasi-Poisson family to estimate the association of interest with daily CVD admissions as outcome and daily influenza admissions as predictor, while controlling for meteorological factors (i.e. temperature, relative humidity, wind speed and total rainfall) and respiratory pollutants (i.e. nitrogen dioxide, sulphur dioxide, ozone and PM₁₀). Results were expressed in the form of relative risk (RR).

RESULTS

Using median as the reference value, a U-shaped association was observed between CVD admissions and temperature. A slight decrease in RR was detected mainly towards the lower end of the temperature scale after adjusting for influenza admissions. Risk of CVD admission was found to be positively associated with the number of influenza hospitalization cases; this association remained consistent and statistically significant across subgroups of age except for those aged 5-49 years.

CONCLUSION

The slight reduction in CVD admission risk towards the lower end of the temperature scale after controlling for influenza activity might be attributed to the winter peaks of influenza, meaning that the effect of low temperature on CVD admissions might be partly mediated by influenza infection. In summary, this study reassures us that ambient temperature is independently associated with CVD hospital admissions and offers support for a positive association between seasonal influenza activity and cardiovascular events in Hong Kong.

The effect of ambient temperature on cardiovascular mortality in 27 Brazilian cities

BACKGROUND

There is limited evidence on the relationship between temperature and cardiovascular mortality in middle and low-income countries, particularly in Latin America. In this study, we investigated the total effect of temperature on cardiovascular mortality in 27 Brazilian cities, and the effect modification by geographic, socioeconomic, demographic and infrastructure characteristics within cities.

METHODS

In the city-specific analysis, we used time-series analyses to estimate the relationship between mean temperature and daily cardiovascular mortality using quasi-Poisson generalized linear models combined with distributed lag non-linear models. In the second stage, a meta-analysis was used to pool the effects of temperature on cardiovascular mortality for Brazil and its five regions (Central-West, North, Northeast, South, and Southeast). We used a meta-regression to examine the effect modification of city-specific geographic, socioeconomic, demographic and infrastructure-related variables.

RESULTS

The risks associated with temperature varied across the locations. Higher cardiovascular mortality was associated with low and high temperatures in most of the cities, Brazil and the Central-West, North, South, and Southeast regions. The overall relative risk (RR) for Brazil was 1.26 (95% confidence interval [CI]: 1.17-1.35) for the 1st percentile of temperature and 1.07 (95% CI: 1.01-1.13) for the 99th percentile of temperature versus the 79th percentile (27.7 °C), where RR was lowest. The temperature range was the variable that best explained the variation in effects among the cities, with greater effects in locations having a broader range.

CONCLUSIONS

The results indicate effects of low and high temperatures on the risk of cardiovascular mortality in most of Brazil's capital cities, besides a pooled effect for Brazil and the Central-West, North, South, and Southeast regions. These findings can help inform public policies addressing the health impact of temperature extremes, especially in the context of climate change.

Acute and Subacute Triggers of Cardiovascular Events

Inability to predict short-term cardiovascular (CV) events and take immediate preemptive actions has long been the Achilles heel of cardiology. However, certain triggers of these events have come to light. Although these triggers are nonspecific and are part of normal life, studying their temporal relationship with the onset of CV events provides an opportunity to alert high-risk atherosclerotic patients who may be most vulnerable to such triggers, the "vulnerable patient". Herein, we review the literature and shed light on the epidemiology and underlying pathophysiology of different triggers. We describe that certain adrenergic triggers can precipitate a CV event within minutes or hours; whereas triggers that elicit an immune or inflammatory response such as infections may tip an asymptomatic "vulnerable patient" to become symptomatic days and weeks later. In conclusion, healthcare providers should counsel high-risk CV patients (e.g., in secondary prevention clinics or those with coronary artery Calcium >75th percentile) on the topic, advise them to avoid such triggers, take protective measures once exposed, and seek emergency care immediately after becoming symptomatic after such triggers. Furthermore, clinical trials targeting triggers (prevention or intervention) are needed.

Association between ambient temperature and mortality risk and burden: time series study in 272 main Chinese cities

OBJECTIVES

To examine the association between temperature and cause specific mortality, and to quantify the corresponding disease burden attributable to non-optimum ambient temperatures.

DESIGN

Time series analysis.

SETTING

272 main cities in China.

POPULATION

Non-accidental deaths in 272 cities covered by the Disease Surveillance Point System of China, from January 2013 to December 2015.

MAIN OUTCOMES AND MEASURES

Daily numbers of deaths from all non-accidental causes and main cardiorespiratory diseases. Potential effect modifiers included demographic, climatic, geographical, and socioeconomic characteristics. The analysis used distributed lag non-linear models to estimate city specific associations, and multivariate meta-regression analysis to obtain the effect estimates at national and regional levels.

RESULTS

1 826 186 non-accidental deaths from total causes were recorded in the study period. Temperature and mortality consistently showed inversely J shaped associations. At the national average level, relative to the minimum mortality temperature (22.8°C, 79.1st centile), the mortality risk of extreme cold temperature (at -1.4°C, the 2.5th centile) lasted for more than 14 days, whereas the risk of extreme hot temperature (at 29.0°C, the 97.5th centile) appeared immediately and lasted for two to three days. 14.33% of non-accidental total mortality was attributable to non-optimum temperatures, of which moderate cold (ranging from -1.4 to 22.8°C), moderate heat (22.8 to 29.0°C), extreme cold (-6.4 to -1.4°C), and extreme heat (29.0 to 31.6°C) temperatures corresponded to attributable fractions of 10.49%, 2.08%, 1.14%, and 0.63%, respectively. The attributable fractions were 17.48% for overall cardiovascular disease, 18.76% for coronary heart disease, 16.11% for overall stroke, 14.09% for ischaemic stroke, 18.10% for haemorrhagic stroke, 10.57% for overall respiratory disease, and 12.57% for chronic obstructive pulmonary diseases. The mortality risk and burden were more prominent in the temperate monsoon and subtropical monsoon climatic zones, in specific subgroups (female sex, age ≥75 years, and ≤9 years spent in education), and in cities characterised by higher urbanisations rates and shorter durations of central heating.

CONCLUSIONS

This nationwide study provides a comprehensive picture of the non-linear associations between ambient temperature and mortality from all natural causes and main cardiorespiratory diseases, as well as the corresponding disease burden that is mainly attributable to moderate cold temperatures in China. The findings on vulnerability characteristics can help improve clinical and public health practices to reduce disease burden associated with current and future abnormal weather.

Time series models of environmental exposures: Good predictions or good understanding

Time series data are popular in environmental epidemiology as they make use of the natural experiment of how changes in exposure over time might impact on disease. Many published time series papers have used parameter-heavy models that fully explained the second order patterns in disease to give residuals that have no short-term autocorrelation or seasonality. This is often achieved by including predictors of past disease counts (autoregression) or seasonal splines with many degrees of freedom. These approaches give great residuals, but add little to our understanding of cause and effect. We argue that modelling approaches should rely more on good epidemiology and less on statistical tests. This includes thinking about causal pathways, making potential confounders explicit, fitting a limited number of models, and not over-fitting at the cost of under-estimating the true association between exposure and disease.